\section{Introduction}
\label{sec:introduction}

LPL is a common MAC-layer technique adopted in Wireless Sensor Networks (WSNs) for reducing energy consumption.
Nodes work in LPL periodically wake up and perform Clear Channel Assessment (CCA) to check whether there is active channel acitivity
A common implementation of CCA in WSNs is detecting whether the channel's energy level exceeds some threshold or not, which is known as \emph{energy detection}.
Namely, a CCA check will regard channel as busy if energy on the channel exceeds the threshold, or idle otherwise.
If channel is busy, nodes remain awake for potential packets; otherwise, nodes go back to sleep.
Under unsynchronized networks, sender is aware of the receiver's wakeup interval but not exact wakeup time.
Hence, sender transmits a preamble stream at least as long as the receiver's wakeup interval for ensuring the receiver could sample this channel activity and wake up.
This process is shown in Figure \ref{fig:lpl}.

The unlicensed 2.4GHz ISM band embraces numerous wireless technologies.
However, the technologies operated on it usually does not include design of tolerating other technologies.
This makes cross-technology radio interference becomes an increasing problem for low-power WSNs.
ZigBee devices have to share the unlicensed spectrum with a variety of other devices such as WiFi devices, Buletooth headsets, microwave oven, cordless phones and various game controllers.
Each such device can lead to interference to ZigBee's communication since ZigBee's underlaying standard (IEEE 802.15.4) has no explicit mechanism to recognize non-ZigBee interference.

In these noisy wireless environments, LPL is susceptible to frequent false wakeups, which is shown in \cite{bib:IPSN13EnergyLPL}.
The false wakeup problem refers to that nodes remain awake even when no packet is transmitting, causing increase of node's duty cycle and unnecessary energy consumption.
Hence, existing CCA is not energy efficient, albeit effective to wake up nodes.
The false wakeup problem arises from the fact that the threshold behavior of existing CCA is too frigile to the noise.
%Most works use fixed threshold which is easily exceeded when other wireless signals exist.
%Recent work \cite{bib:IPSN13EnergyLPL} notices this shortcoming and proposes an adaptive energy detection protocol which adaptively adjusts the threshold of CCA to avoid the noise waking up nodes.
To make sure no packet is ignored, the maximum CCA threshold could be adopted is smaller than the weakest strength of effective ZigBee signal.
Therefore, no matter how well the threshold is set, false wakeups problem is inevitable when the strength of the noise is stronger than minimum received signal strength of incoming links.
Given this, existing methods are greatly limited, particulary in noisy deployments such as indoor WSNs.
%We analyze the performance of existing threshold-based methods in Section \ref{sec:empiricalStudy}.
%The detail analysis of the threshold-based methods is presented in Section \ref{sec:empiricalStudy}.

\begin{figure}[t]
\centering
\includegraphics[width=2.7in]{figure/LPL.pdf}
\caption{Working procedure of LPL}
\label{fig:lpl}
\end{figure}

\begin{figure}[t]
\centering
\includegraphics[width=2.7in]{figure/LPP.pdf}
\caption{Working procedure of LPP}
\label{fig:lpp}
\end{figure}

To address the false wakeup problem that threshold-based CCA cannot settle thoroughly, we propose Interference-Aware LPL (IALPL), a novel approach which is beyond the threshold behavior of existing methods.
%aware of existence of interference. the composing technologies of the on-going transmissions.
It is motivated by the key insight that energy efficient LPL should wake up nodes only when there is an on-going ZigBee packet, rather than when there is energy on channel.
% and make nodes sleep otherwise.
Beyond the threshold, IALPL adopts characteristic RSSI sequences of different wireless technologies operated in 2.4GHz to distinguish ZigBee from others and assesses the channel is busy because of ZigBee or other technologies.
Only when ZigBee signal is detected, IALPL regards channel busy and wakes up node to receive this potential packet.
However, distinguishing ZigBee in a short time is non-trivial due to the various co-existing wireless technologies in 2.4GHz.
IALPL abstracts several key features to accurately classify ZigBee and non-ZigBee RSSI patterns.
IALPL also adopts online CCA deciding algorithm to judge whether there is ZigBee or not in several milliseconds.


%Existing threshold-based CCA fail because they cannot differentiate ZigBee and non-ZigBee signals.
%Thus, they have the false wakeup problem when non-ZigBee signal with RSSI stronger than the threshold exists.

In contrast to previous studies which are all threshold-based, IALPL is a method beyond the threshold.
%this paper investigates the shortcomings of threshold-based methods and proposes a method beyond the threshold.
%To our best knowledge, this paper presents the first study about illustration of shortcomings of threshold-based CCA methods from the perspective of criterion about busy channel.
It refines the criterion of busy channel in CCA used in wakeup procedure of LPL as "\emph{Judging there is \textbf{energy} on the channel or not}" instead of "\emph{Judging there is \textbf{ZigBee transmitting} on the channel or not}".
%Therefore, IALPL is energy-minimizing by waking up nodes only when ZigBee signal is detected.
Specifically, the main contributions of this paper is as follows.

(1) Illustration of the significant shortcomings of threshold-based CCA checks and demonstration the potential benefits of being aware of what technologies the on-going transmissions is composed of.

(2) An empirical study demonstrates the feasibility of using characteristic RSSI sequences to distinguish ZigBee signal from the others in a short time.
%(I don't have faith to say this since SoNIC)To our best knowledge, this is the first detailed study about the RSSI sequences' differences of ZigBee and Non-ZigBee signal from the microcosmic behaviors.

(3) IALPL, an interference-aware LPL protocol that wakes up nodes only when ZigBee signal is detected to improve the energy efficiency of WSNs.

The remaining of the paper is organized as follows.
Section \ref{sec:relatedWork} compares IALPL with related works.
Section \ref{sec:motivation} describes the motivations of this paper.
Section \ref{sec:empiricalStudy} empirically studies the characters of RSSI sequences of different wireless technologies operated in 2.4GHz band and demonstrates the feasibility of using characteristic RSSI sequences to distinguish ZigBee signal from the others.
Section \ref{sec:design} elaborates the design of IALPL tailored for energy-minimizing LPL with minimum false wakeups.
Section \ref{sec:implementation} presents the implementation of IALPL on TelosB platform.
Section \ref{sec:evaluation} evaluates IALPL in both controlled and office environments.
Finally, Section \ref{sec:conclusion} concludes this paper.

